{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 图可视化\n",
    "\n",
    "WebKB 数据集包括了图，用networkx等包可视化，最好是Gephi的三维可视化。\n",
    "\n",
    "Gephi 支持的图格式：\n",
    "https://gephi.org/users/supported-graph-formats/\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "EdgeView([(0, 1), (0, 2), (0, 3), (0, 4), (1, 2), (1, 3), (1, 4), (2, 3), (2, 4), (3, 4)])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import networkx as nx\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "G = nx.complete_graph(5)\n",
    "G.edges"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NodeView((0, 1, 2, 3, 4))"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "G.nodes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nx.draw(G)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "nx.from_numpy_matrix\n",
    "nx.from_numpy_array\n",
    "nx.from_scipy_sparse_matrix"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 开始画图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import "
   ]
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "2497819141e8ba68491e095adc461a03e742be7ecd39014decbc2aa0e30dc29f"
  },
  "kernelspec": {
   "display_name": "Python 3.9.10 64-bit (windows store)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.10"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
